On Sun, Jan 12, 2014 at 2:47 PM, Peter Brawley
<peter.brawley@stripped> wrote:
> On 2014-01-12 1:17 PM, Larry Martell wrote:
>>
>> I've been asked to do something that I do not think is possible in SQL.
>>
>> I have a query that has this basic form:
>>
>> SELECT a, b, c, d, AVG(e), STD(e), CONCAT(x, ',', y) as f
>> FROM t
>> GROUP BY a, b, c, d, f
>>
>> x and y are numbers (378.18, 2213.797 or 378.218, 2213.949 or
>> 10053.490, 2542.094).
>>
>> The business issue is that if either x or y in 2 rows that are in the
>> same a, b, c, d group are within 1 of each other then they should be
>> grouped together. And to make it more complicated, the tolerance is
>> applied as a rolling continuum. For example, if the x and y in a set
>> of grouped rows are:
>>
>> row 1: 1.5, 9.5
>> row 2: 2.4, 20.8
>> row 3: 3.3, 40.6
>> row 4: 4.2, 2.5
>> row 5: 5.1, 10.1
>> row 6: 6.0, 7.9
>> row 7: 8.0, 21.0
>> row 8: 100, 200
>>
>> 1 through 6 get combined because all their X values are within the
>> tolerance of some other X in the set that's been combined. 7's Y value
>> is within the tolerance of 2's Y, so that should be combined as well.
>> 8 is not combined because neither the X or Y value is within the
>> tolerance of any X or Y in the set that was combined.
>>
>> In python I can easily parse the data and identify the rows that need
>> to be combined, but then I've lost the ability to calculate the
>> average and std. The only way I can think of to do this is to remove
>> the grouping from the SQL and do all the grouping and aggregating
>> myself. But this query often returns 20k to 30k rows after grouping.
>> It could easily be 80k to 100k rows that I have to process if I remove
>> the grouping and I think that will be very slow.
>>
>> Anyone have any ideas?
>
>
> Could you compute the row-to-row values & write them to a temp table, then
> run the SQL that incorporates that result column?
I thought of temp tables, but I could not come up with a way to use
them for this. How can I apply the x/y tolerance grouping in sql?

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